Using Large-Scale Assessment Datasets for Research in Science and Mathematics Education: Programme for International Student Assessment (PISA)
Large-scale assessments of student achievement provide a window into the broadly defined concepts of literacy and generate information about levels and types of student achievement in relation to some of the correlates of learning, such as student background, attitudes, and perceptions, and perhaps...
| Main Authors: | , , , , |
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| Format: | Journal Article |
| Published: |
Springer
2007
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| Online Access: | http://hdl.handle.net/20.500.11937/43375 |
| _version_ | 1848756673982758912 |
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| author | Anderson, J. Lin, H. Treagust, David Ross, S. Yore, L. |
| author_facet | Anderson, J. Lin, H. Treagust, David Ross, S. Yore, L. |
| author_sort | Anderson, J. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Large-scale assessments of student achievement provide a window into the broadly defined concepts of literacy and generate information about levels and types of student achievement in relation to some of the correlates of learning, such as student background, attitudes, and perceptions, and perhaps school and home characteristics. This paper provides an overview and outlines potential research opportunities of one such assessment—the Programme for International Student Assessment (PISA). In order to provide examples of the work that can be accomplished with these data, we describe and discuss the results generated from PISA 2000 and PISA 2003 in terms of international comparisons of achievement and the models of relational patterns of student, home, and school characteristics. We provide insight from the recent pilot testing conducted in Taiwan for PISA 2006, which has a focus on scientific literacy. This is followed by a discussion of the implications and potentials of the 2000 and 2003 datasets to facilitate research on scientific and mathematical literacy. The paper concludes with a look ahead to PISA 2006 and what researchers should be attending to in the research reports generated from the OECD and the research interests that they could follow given access to the datasets generated. |
| first_indexed | 2025-11-14T09:15:57Z |
| format | Journal Article |
| id | curtin-20.500.11937-43375 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:15:57Z |
| publishDate | 2007 |
| publisher | Springer |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-433752017-09-13T15:33:38Z Using Large-Scale Assessment Datasets for Research in Science and Mathematics Education: Programme for International Student Assessment (PISA) Anderson, J. Lin, H. Treagust, David Ross, S. Yore, L. future opportunities secondary analyses large-scale assessments PISA results Large-scale assessments of student achievement provide a window into the broadly defined concepts of literacy and generate information about levels and types of student achievement in relation to some of the correlates of learning, such as student background, attitudes, and perceptions, and perhaps school and home characteristics. This paper provides an overview and outlines potential research opportunities of one such assessment—the Programme for International Student Assessment (PISA). In order to provide examples of the work that can be accomplished with these data, we describe and discuss the results generated from PISA 2000 and PISA 2003 in terms of international comparisons of achievement and the models of relational patterns of student, home, and school characteristics. We provide insight from the recent pilot testing conducted in Taiwan for PISA 2006, which has a focus on scientific literacy. This is followed by a discussion of the implications and potentials of the 2000 and 2003 datasets to facilitate research on scientific and mathematical literacy. The paper concludes with a look ahead to PISA 2006 and what researchers should be attending to in the research reports generated from the OECD and the research interests that they could follow given access to the datasets generated. 2007 Journal Article http://hdl.handle.net/20.500.11937/43375 10.1007/s10763-007-9090-y Springer restricted |
| spellingShingle | future opportunities secondary analyses large-scale assessments PISA results Anderson, J. Lin, H. Treagust, David Ross, S. Yore, L. Using Large-Scale Assessment Datasets for Research in Science and Mathematics Education: Programme for International Student Assessment (PISA) |
| title | Using Large-Scale Assessment Datasets for Research in Science and Mathematics Education: Programme for International Student Assessment (PISA) |
| title_full | Using Large-Scale Assessment Datasets for Research in Science and Mathematics Education: Programme for International Student Assessment (PISA) |
| title_fullStr | Using Large-Scale Assessment Datasets for Research in Science and Mathematics Education: Programme for International Student Assessment (PISA) |
| title_full_unstemmed | Using Large-Scale Assessment Datasets for Research in Science and Mathematics Education: Programme for International Student Assessment (PISA) |
| title_short | Using Large-Scale Assessment Datasets for Research in Science and Mathematics Education: Programme for International Student Assessment (PISA) |
| title_sort | using large-scale assessment datasets for research in science and mathematics education: programme for international student assessment (pisa) |
| topic | future opportunities secondary analyses large-scale assessments PISA results |
| url | http://hdl.handle.net/20.500.11937/43375 |